





def      lowerCamelCase__      (__lowerCamelCase						):
     _SCREAMING_SNAKE_CASE							:						List[Any]         =				len(SCREAMING_SNAKE_CASE__						)
     _SCREAMING_SNAKE_CASE							:						Union[str, Any]         =				sum(SCREAMING_SNAKE_CASE__						)

     _SCREAMING_SNAKE_CASE							:						Tuple         =				[[False for x in range(s + 1						)] for y in range(n + 1						)]

     for i in range(1,							n + 1						):
          _SCREAMING_SNAKE_CASE							:						int         =				True

     for i in range(1,							s + 1						):
          _SCREAMING_SNAKE_CASE							:						Union[str, Any]         =				False

     for i in range(1,							n + 1						):
          for j in range(1,							s + 1						):
               _SCREAMING_SNAKE_CASE							:						int         =				dp[i][j - 1]

               if arr[i - 1] <= j:
                    _SCREAMING_SNAKE_CASE							:						Tuple         =				dp[i][j] or dp[i - 1][j - arr[i - 1]]

     for j in range(int(s / 2						),							-1,							-1						):
          if dp[n][j] is True:
               _SCREAMING_SNAKE_CASE							:						List[str]         =				s - 2 * j
               break

     return diff



'''simple docstring'''


from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_						:  str				  =						logging.get_logger(__name__)

UpperCAmelCase_						:  Optional[int]				  =						{
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}





class        lowercase__    (		_snake_case   ):





							'''simple docstring'''


							A_				: List[str]       =    """lilt"""






							def __init__(       self       ,   __snake_case=3_0522       ,   __snake_case=768       ,   __snake_case=12       ,   __snake_case=12       ,   __snake_case=3072       ,   __snake_case="gelu"       ,   __snake_case=0.1       ,   __snake_case=0.1       ,   __snake_case=512       ,   __snake_case=2       ,   __snake_case=0.02       ,   __snake_case=1e-12       ,   __snake_case=0       ,   __snake_case="absolute"       ,   __snake_case=None       ,   __snake_case=4       ,   __snake_case=1024       ,   **__snake_case       ,   ):
											super().__init__(pad_token_id=__snake_case       ,   **__snake_case    )

											_SCREAMING_SNAKE_CASE					:			str							= vocab_size
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= hidden_size
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= num_hidden_layers
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= num_attention_heads
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= hidden_act
											_SCREAMING_SNAKE_CASE					:			Dict							= intermediate_size
											_SCREAMING_SNAKE_CASE					:			Tuple							= hidden_dropout_prob
											_SCREAMING_SNAKE_CASE					:			List[str]							= attention_probs_dropout_prob
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= max_position_embeddings
											_SCREAMING_SNAKE_CASE					:			Dict							= type_vocab_size
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= initializer_range
											_SCREAMING_SNAKE_CASE					:			Tuple							= layer_norm_eps
											_SCREAMING_SNAKE_CASE					:			str							= position_embedding_type
											_SCREAMING_SNAKE_CASE					:			List[str]							= classifier_dropout
											_SCREAMING_SNAKE_CASE					:			int							= channel_shrink_ratio
											_SCREAMING_SNAKE_CASE					:			str							= max_ad_position_embeddings




